Research on Automatic Parking System Strategy
Abstract
:1. Introduction
2. The Initialization Program
2.1. Vehicle Kinematics Model
2.2. Kinematic Constraints
2.3. Boundary Conditions
2.4. Weighted Ring Graph
3. Parking Path Planning
3.1. Bidirectional Breadth-First Search Design Based on Parking Environment
3.2. Traditional Bellman–Ford Algorithm
3.3. Modified Bellman–Ford Algorithm
3.4. Parking Paths Smooth
- (1)
- The zero-th boundary condition. The condition satisfies the relation: .
- (2)
- The first boundary condition. At the endpoint, the first derivative is given, and if and , the following relationship is satisfied.
- (3)
- The second boundary condition. For the second derivative of a given endpoint, if and , the following relation can be deduced.
4. Results and Discussion
4.1. Comparison of Experimental Results between Proposed Automatic Parking System and Traditional Path Planning Strategy
4.2. Comparison of Experimental Results between Proposed Automatic Parking System and Similar Path Planning Strategy
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Item | Parameter | |
---|---|---|
Experimental vehicle parameters | Width/Wd | 17.8 cm |
Wheel base/hm | 19.4 cm | |
Length/L | 28.5 cm | |
Distance between front wheel axle and nose/Lbegin | 5.4 cm | |
Distance between rear axle and rear axle/Lend | 2.5 cm | |
Minimum turning radius/Rmin | 33.28 cm | |
Experimental site parameters | Length/Cow | 118.9 cm |
Width/Col | 84.1 cm | |
Number of parking Spaces available | 1 | |
Boundary condition | One side of the parking space is shielded with a height of about 40 cm |
Traditional | Proposed | |||||||
---|---|---|---|---|---|---|---|---|
Experiment Conditions | Actual Success Rate | Ideal Success Rate | Average Vehicle Moving Time (s) | Average Algorithm Running Time (ms) | Actual Success Rate | Ideal Success Rate | Average Vehicle Moving Time (s) | Average Algorithm Running Time (ms) |
Ideal conditions | 86.7% | 90.0% | 47.3743 | 1.010 | 84.3% | 100% | 47.2273 | 7297.2 |
General complex conditions | 60.0% | 73.3% | 44.7203 | 1.003 | 63.3% | 90.0% | 45.0593 | 7870.1 |
Extremely complex conditions | 0.0% | 53.3% | 47.9330 | 1.001 | 23.3% | 66.7% | 50.2448 | 10,599.4 |
n, m | The Similar Method | The Proposed Strategy | ||
---|---|---|---|---|
Step Number | Computing Time (ms) | Step Number | Computing Time (ms) | |
82 | 3.75 | 78 | 732.11 | |
86 | 4.09 | 86 | 783.56 | |
91 | 5.21 | 89 | 964.29 | |
91 | 5.87 | 90 | 981.01 | |
94 | 6.88 | 89 | 1035.22 | |
99 | 7.55 | 92 | 1104.21 | |
108 | 7.92 | 101 | 1326.89 | |
113 | 9.69 | 104 | 1568.53 | |
121 | 10.63 | 115 | 1925.16 | |
130 | 12.01 | 120 | 2011.05 |
n, m | The Similar Method | The Proposed Strategy | ||
---|---|---|---|---|
Step Number | Computing Time (ms) | Step Number | Computing Time (ms) | |
96 | 5.23 | 91 | 812.25 | |
105 | 7.86 | 100 | 901.02 | |
121 | 8.05 | 119 | 1021.01 | |
133 | 9.42 | 121 | 1125.69 | |
145 | 10.21 | 136 | 1368.53 | |
151 | 11.85 | 141 | 1685.57 | |
167 | 12.05 | 157 | 1956.58 | |
187 | 15.36 | 174 | 2012.55 | |
192 | 17.69 | 182 | 2114.09 | |
201 | 19.62 | 191 | 2456.38 |
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Zhang, C.; Zhou, R.; Lei, L.; Yang, X. Research on Automatic Parking System Strategy. World Electr. Veh. J. 2021, 12, 200. https://doi.org/10.3390/wevj12040200
Zhang C, Zhou R, Lei L, Yang X. Research on Automatic Parking System Strategy. World Electric Vehicle Journal. 2021; 12(4):200. https://doi.org/10.3390/wevj12040200
Chicago/Turabian StyleZhang, Chuanwei, Rui Zhou, Lei Lei, and Xinyue Yang. 2021. "Research on Automatic Parking System Strategy" World Electric Vehicle Journal 12, no. 4: 200. https://doi.org/10.3390/wevj12040200